AI can make more content. You still need something to say.
The feed will not run out of content. The question is why anyone should spend their time on yours.
ORIGINAL EPISODE: Personligt varumärke, nya EU-krav & AI för annonsköp #118 · · Audio in Swedish
Who does the content reach, and what do they take away? In episode 118, I describe the difference between LinkedIn posts with broad appeal and questions from people working in ecommerce. Fredrik Ankarsköld and I also discuss AI for research, analysis and video. Someone still needs to choose the topic, check the evidence and decide when the task is finished.
People get to know you before you meet.
For me, a personal brand starts with people understanding what you know and what you stand for. You share something useful, do it again and let people form an opinion over time. When you finally meet, the conversation does not have to start from zero.
It does not have to mean being recognised by everyone. In the podcast, we discuss the value of being known in your own niche. A handful of people working on the same questions can be a very worthwhile audience to reach. That also applies if you are employed, looking for your next role or finding your direction.
There is work behind this. You need something to contribute and the willingness to share it regularly. A profile photo and a new LinkedIn title do very little of that work.
Listen at this point · 00:24I look at who gets in touch.
Fredrik raises the difference between videos that get the most views and those that generate revenue. General advice can suit a great many people. That says little about how many of them need what you sell.
I recognise this from my own content. In the conversation, I describe how LinkedIn posts with broad appeal reached far beyond the core audience without generating much inbound interest. When content around the podcast started prompting questions from people actually working in ecommerce, the response meant something different.
That does not make reach uninteresting. A broad video can lead someone to a more detailed discussion. But I want to understand what happens after the view: which questions do we get, who comes back and what do they seem to have taken away?
Listen at this point · 03:46I want to show what the work actually looks like.
I had international role models when I was trying to learn growth and ecommerce. I looked for knowledge, contacted people and wanted to understand their thinking. That experience is part of why I want to share more of entrepreneurship behind the scenes.
There is frustration too. In the episode, I am quite critical of marketing that uses a displayed lifestyle to sell young people a shortcut. My objection concerns that selling and the expectations it creates. We also make clear in the conversation that good courses do exist.
I want to show the decisions, work and lessons that come with building product brands. It is the material I wanted when I was trying to understand the industry. If someone can use the thinking in their own business, I have something worth continuing to share.
Listen at this point · 07:19Give AI a job that already needs doing.
When we turn to AI, I use creative research as a concrete example. Before a creative meeting, someone needs to understand what is happening in the category, which questions customers ask and which formats other brands are testing. That is a real, recurring task to start with.
In the podcast, I describe how reviews can offer clues to both valued features and problems. Ads from other markets can inspire an approach of your own. The finished research needs to help the team choose what to investigate and produce.
We also need to distinguish a signal from a conclusion. A competitor’s ad running for a long time is worth a closer look. It does not give us access to their profitability. Research becomes useful when we understand what the evidence can actually tell us.
Listen at this point · 34:45Decide which business question AI should answer.
In the conversation, I am very positive about AI doing the work. At the same time, I am clear that strategy, setting goals, methodology and choosing creative still take work. Someone needs to define the task and understand the business it should help.
Take the question of which product is best at bringing in new customers. Best could mean high sales on the first purchase. It could also mean the customer returns more often and buys across more of the range. The question you ask affects what the answer gives you reason to do with marketing.
The same applies to ads. I describe the risk of assessing each ad in isolation and missing how the material works together. An account can look different when you remove something that created interest earlier in the customer journey. A finished answer therefore needs to be discussed in context.
Listen at this point · 40:08Write down what has to be finished.
One of the most practical discussions in the episode concerns giving agents tasks. A goal can sound clear to the person setting it and still be too open for whoever has to do the work. The work can then continue without producing anything more useful.
Fredrik suggests a checklist as a way to make the task more concrete. I connect that to checking the result. If the work concerns a service people will use, looking logical in the code is not enough. It also needs to work for someone encountering it for the first time.
Write down which deliverables must be ready and how they will be checked. We also discuss resource limits, so an unclear agent task does not keep costing money while it looks for more things to do.
Listen at this point · 48:13A realistic video still needs a good idea.
Towards the end, we look at AI-generated video. In one ad, I am impressed by how well the images and movement hold together. Fredrik makes a useful distinction: the execution can be convincing while the hook and ad idea feel generic.
That is where much of the work lies. As technology handles more of production, we need to take greater care over what the customer should understand, the reason we give her to stop and what the material should achieve.
When assessing your next AI video, look again once you have stopped being impressed by the technology. What does the opening say? What does the customer learn? What reason does the film give her to choose the product? That was where we found weaknesses in the example.
Listen at this point · 54:54This article is based on the conversation and adapted for reading.